Big data clusters often comprise of hundreds to thousands of machines running applications in concert. While many such clusters are built on commodity hardware, some run on custom appliances for better application performance and manageability. The appliance vendors build these custom appliances from hardware procured from different and/or multiple manufacturers. A big data cluster may comprise up to thousands of such appliances with hardware components from different hardware vendors. Typically, firmware for hardware in a cluster is manually loaded for each piece of hardware. This is very time consuming task when there are hundreds to thousands of machines. Supporting the appliances can be a very complex, tedious, slow and error-prone process.